Neonicotinoid insecticides have come under scrutiny for their potential unintended effects on non-target organisms, particularly pollinators in agro-ecosystems. As part of a larger study of neonicotinoid residues associated with maize (corn) production, 76 water samples within or around the perimeter of 18 commercial maize fields and neighbouring apiaries were collected in 5 maize-producing counties of southwestern Ontario. Residues of clothianidin (mean = 2.28, max. = 43.60 ng/mL) and thiamethoxam (mean = 1.12, max. = 16.50 ng/mL) were detected in 100 and 98.7% of the water samples tested, respectively. The concentration of total neonicotinoid residues in water within maize fields increased six-fold during the first five weeks after planting, and returned to pre-plant levels seven weeks after planting. However, concentrations in water sampled from outside the fields were similar throughout the sampling period. Soil samples from the top 5 cm of the soil profile were also collected in these fields before and immediately following planting. The mean total neonicotinoid residue was 4.02 (range 0.07 to 20.30) ng/g, for samples taken before planting, and 9.94 (range 0.53 to 38.98) ng/g, for those taken immediately after planting. Two soil samples collected from within an conservation area contained detectable (0.03 and 0.11 ng/g) concentrations of clothianidin. Of three drifted snow samples taken, the drift stratum containing the most wind-scoured soil had 0.16 and 0.20 ng/mL mainly clothianidin in the melted snow. The concentration was at the limit of detection (0.02 ng/mL) taken across the entire vertical profile. With the exception of one sample, water samples tested had concentrations below those reported to have acute, chronic or sublethal effects to honey bees. Our results suggest that neonicotinoids may move off-target by wind erosion of contaminated soil. These results are informative to risk assessment models for other non-target species in maize agro-ecosytems.

BackgroundSelection of pesticides with small ecological footprints is a key factor in developing sustainable agricultural systems. Policy guiding the selection of pesticides often emphasizes natural products and organic-certified pesticides to increase sustainability, because of the prevailing public opinion that natural products are uniformly safer, and thus more environmentally friendly, than synthetic chemicals.Methodology/Principal FindingsWe report the results of a study examining the environmental impact of several new synthetic and certified organic insecticides under consideration as reduced-risk insecticides for soybean aphid (Aphis glycines) control, using established and novel methodologies to directly quantify pesticide impact in terms of biocontrol services. We found that in addition to reduced efficacy against aphids compared to novel synthetic insecticides, organic approved insecticides had a similar or even greater negative impact on several natural enemy species in lab studies, were more detrimental to biological control organisms in field experiments, and had higher Environmental Impact Quotients at field use rates.Conclusions/SignificanceThese data bring into caution the widely held assumption that organic pesticides are more environmentally benign than synthetic ones. All pesticides must be evaluated using an empirically-based risk assessment, because generalizations based on chemical origin do not hold true in all cases.

Using neonicotinoid insecticides as seed treatments is a common practice in field crop production. Exposure of nontarget organisms to neonicotinoids present in various environmental matrices is debated. In the present study, concentrations of neonicotinoid residues were measured in the top 5 cm of soil and overlying soil surface dust before planting in 25 commercial fields with a history of neonicotinoid seed treatment use in southwestern Ontario in 2013 and 2014 using liquid chromatography-electrospray ionization tandem mass spectrometry. The mean total concentrations were 3.05 ng/g and 47.84 ng/g in 2013 and 5.59 ng/g and 71.17 ng/g in 2014 for parent soil and soil surface dust, respectively. When surface and parent soil residues were compared the mean concentration in surface dust was 15.6-fold and 12.7-fold higher than that in parent soil in 2013 and 2014, respectively. Pooled over years, the surface dust to parent soil ratio was 13.7, with mean concentrations of 4.36 ng/g and 59.86 ng/g for parent soil and surface dust, respectively. The present study's results will contribute important knowledge about the role these residues may play in the overall risk assessment currently under way for the source, transport, and impact of neonicotinoid insecticide residues in a maize ecosystem.

Neonicotinoid insecticides, especially as seed treatments, have raised concerns about environmental loading and impacts on pollinators, biodiversity, and ecosystems. The authors measured concentrations of neonicotinoid residues in the top 5 cm of soil before planting of maize (corn) in 18 commercial fields with a history of neonicotinoid seed treatment use in southwestern Ontario in 2013 and 2014 using liquid chromatography-tandem mass spectrometry with electrospray ionization. A simple calculator based on first-order kinetics, incorporating crop rotation, planting date, and seed treatment history from the subject fields, was used to estimate dissipation rate from the seed zone. The estimated half-life (the time taken for 50% of the insecticide to have dissipated by all mechanisms) based on 8 yr of crop history was 0.64 (range, 0.25-1.59) yr and 0.57 (range, 0.24-2.12) yr for 2013 and 2014, respectively. In fields where neonicotinoid residues were measured in both years, the estimated mean half-life between 2013 and 2014 was 0.4 (range, 0.27-0.6) yr. If clothianidin and thiamethoxam were used annually as a seed treatment in a typical crop rotation of maize, soybean, and winter wheat over several years, residues would plateau rather than continue to accumulate. Residues of neonicotinoid insecticides after 3 yr to 4 yr of repeated annual use tend to plateau to a mean concentration of less than 6 ng/g in agricultural soils in southwestern Ontario.

Coccinella septempunctata L. and Harmonia axyridis Pallas are key natural enemies of soybean aphid, Aphis glycines Matsumura, in North America. Third instars, adult females, and adult males of both C. septempunctata and H. axyridis exhibited a type II functional response for predation toward adult soybean aphids at 26 +/- 1 degrees C. In C. septempunctata, the functional response curve of adult males differed from those of third instars and adult females, but there was no difference between third instars and adult females. In H. axyridis, the functional response curves of larvae, adult females, and adult males all differed significantly. Third instars and adult females consumed significantly more soybean aphids than did adult males at prey densities of 150 and 180 aphids per arena for C. septempunctata and at prey densities of 60, 90, 120, 150, and 180 aphids per arena for H. axyridis. The theoretical maximum daily predation rate of adult aphids by C. septempunctata was predicted to be 204 per third instar, 277 per adult female, and 166 per adult male, and 244, 156, and 73, respectively, for H. axyridis. Third instars and adult females of both species consumed significantly more aphids than did adult males on soybean plants with the recommended action threshold of 250 soybean aphids per plant. Both C. septempunctata and H. axyridis have high predation capacities and are important in suppressing soybean aphid populations.

This paper describes the relationship between spectral resolution and classification accuracy in analyses of hyperspectral imaging data acquired from crop leaves. The main scope is to discuss and reduce the risk of model over-fitting. Over-fitting of a classification model occurs when too many and/or irrelevant model terms are included (i.e., a large number of spectral bands), and it may lead to low robustness/repeatability when the classification model is applied to independent validation data. We outline a simple way to quantify the level of model over-fitting by comparing the observed classification accuracies with those obtained from explanatory random data. Hyperspectral imaging data were acquired from two crop-insect pest systems: (1) potato psyllid (Bactericera cockerelli) infestations of individual bell pepper plants (Capsicum annuum) with the acquisition of hyperspectral imaging data under controlled-light conditions (data set 1), and (2) sugarcane borer (Diatraea saccharalis) infestations of individual maize plants (Zea mays) with the acquisition of hyperspectral imaging data from the same plants under two markedly different image-acquisition conditions (data sets 2a and b). For each data set, reflectance data were analyzed based on seven spectral resolutions by dividing 160 spectral bands from 405 to 907 nm into 4, 16, 32, 40, 53, 80, or 160 bands. In the two data sets, similar classification results were obtained with spectral resolutions ranging from 3.1 to 12.6 nm. Thus, the size of the initial input data could be reduced fourfold with only a negligible loss of classification accuracy. In the analysis of data set 1, several validation approaches all demonstrated consistently that insect-induced stress could be accurately detected and that therefore there was little indication of model over-fitting. In the analyses of data set 2, inconsistent validation results were obtained and the observed classification accuracy (81.06%) was only a few percentage points above that obtained using random data (66.7-77.4%). Thus, our analysis highlights a potential risk of model over-fitting and emphasizes the importance of testing for this important aspect as part of developing reliable and robust classification models.

The DAT approach has the potential to reduce pesticide use, will help preserve natural enemy populations and can be applied to other pest systems with diverse natural enemy guilds.

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